In an age of disruption, everyone has to adapt eventually. However, the typical organization is ill-suited to change direction. Managers spend years—and sometimes decades—working to optimize their operations to deliver specific outcomes and that can make an organization rigid if the face of a change in the basis of competition.
So it shouldn’t be surprising that the idea of a networked organizations have come into vogue. While hierarchies tend to be rigid, networks are highly adaptable and almost infinitely scalable. Unfortunately, popular organizational schemes such as matrixed management and Holacracy have had mixed results, at best.
The truth is that networks have little to do with an organization chart and much more to do with how informal connections form in your organization, especially among lower-level employees. In fact, coming up with a complex scheme is likely to do little more than cause a lot of needless confusion. Here are the myths you need to avoid.
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In the 1970s and 80s, business investment in computer technology were increasing by more than 20% per year. Strangely though, productivity growth had decreased during the same period. Economists found this turn of events so strange that they called it the productivity paradox to underline their confusion.
Productivity growth would take off in the late 1990s, but then mysteriously drop again during the mid-aughts. At each juncture, experts would debate whether digital technology produced real value or if it was all merely a mirage. The debate would continue even as industry after industry was disrupted.
Today, that debate is over, but a new one is likely to begin over artificial intelligence. Much like in the early 1970s, we have increasing investment in a new technology, diminished productivity growth and “experts” predicting massive worker displacement . Yet now we have history and experience to guide us and can avoid making the same mistakes.
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We live in an age in which change has become the only constant. So it’s not surprising that change management models have become popular. Executives are urged to develop a plan to communicate the need for change, create a sense of urgency and then drive the process through to completion.
Unfortunately, the vast majority of these efforts fail and it’s not hard to see why. Anybody who’s ever been married or had kids knows first-hand how difficult it can be to convince even a single person of something. Any effort to persuade hundreds, if not thousands, of people through some kind of mass effort is setting the bar pretty high.
However, as I explain in Cascades, what you can do is help them convince each other by changing the dynamic so that people enthusiastic about change can influence other (slightly less) enthusiastic people. The truth is that small groups, loosely connected, but united by a shared purpose drive transformational change. So that’s where you need to start.
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In 1928, Alexander Fleming arrived at his lab to find that a mysterious mold had contaminated his Petri dishes and was eradicating the bacteria colonies he was trying to grow. Intrigued, he decided to study the mold. That’s how Fleming came to be known as the discoverer of penicillin.
Fleming’s story is one that is told and retold because it reinforces so much about what we love about innovation. A brilliant mind meets a pivotal moment of epiphany and—Eureka!— the world is forever changed. Unfortunately, that’s not really how things work. It wasn’t true in Fleming’s case and it won’t work for you.
The truth is that innovation is never a single event, but a process of discovery, engineering and transformation, which is why penicillin didn’t become commercially available until 1945 (and the drug was actually a different strain of the mold than Fleming had discovered). We need to stop searching for Eureka moments and get busy with the real work of innovating.
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In 2012, Shaun Wilson and Michael Brett were designing aerospace simulation software. On one particular project, Lockheed Martin’s Chief Scientist, Dr. Ned Allen, mentioned that it had just acquired an early quantum computer from D-Wave Systems, which he thought would help with computational work.
They were impressed. “We found that it was an incredibly promising technology, Brett told me. “We could see the potential to one day do things that just weren’t possible with digital computers, even the high performance systems we were working with.” It was something unlike anything they had ever seen.
“With big data taking off, we saw the need for high performance predictive analytics and thought quantum computing could be a real differentiator. That was the opportunity that led us to think about starting a company,” Brett remembers. Today, the company they founded, QxBranch, is becoming a key player in the race to develop practical quantum applications.
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Peter Thiel likes to point out that we wanted flying cars, but got 140 characters instead. He’s only partly right. For decades futuristic visions showed everyday families zipping around in flying cars and it’s true that even today we’re still stuck on the ground. Yet that’s not because we’re unable to build one. In fact the first was invented in 1934.
The problem is not so much with engineering, but economics, safety and convenience. We could build a flying car if we wanted to, but to make one that can compete with regular cars is another matter entirely. Besides, in many ways, 140 characters are better than a flying car. Cars only let us travel around town, the Internet helps us span the globe.
That has created far more value than a flying car ever could. We often fail to predict the future accurately because we don’t account for our capacity to surprise ourselves, to see new possibilities and take new directions. We interact with each other, collaborate and change our priorities. The future that we predict is never as exciting as the one we eventually create.
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In Who Says Elephants Can’t Dance, the bestselling memoir of the his historic turnaround at IBM, Lou Gerstner wrote, “I came to see, in my time at IBM, culture isn’t just one aspect of the game—It is the game. In the end, an organization is nothing more than the collective capacity of its people to create value.”
There has been endless discussion about whether change should be driven from the top-down or the bottom-up, but that is, for the most part, a red herring. True transformation tends to move side-to-side, driven through horizontal connections among peers. The best way to create change in an organization is to empower it.
That’s why the data giant Experian invested years networking its organization and found that it paid off when it mattered most. While traditional hierarchies waste valuable time and effort pushing orders down the chain of command, networked organizations can adapt to changing market conditions with far more agility. Transformation begins with a networked culture.
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Boeing and Airbus are arch-rivals, competing vigorously over decades for supremacy in the global aviation market, much like DowDupont and BASF do in chemicals. Yet all of these companies, along with many others, collaborate at places like the Composites Institute (IACMI). They do this not out of any altruism, of course, but self-interest.
It is at places like the Composites Institute that profit-driven companies can explore the future with top notch scientists from places like Oak Ridge National Laboratory, Michigan State University and Purdue as well as dozens of smaller companies active in the space. To not participate would be to risk being cut out of important developments.
This type of activity is not entirely new. In the 80s, semiconductor firms, along with the Department of Defense, created SEMATECH to regain competitiveness against foreign competition, while still fighting it out in the marketplace. The truth is that sometimes you need to collaborate and sometimes you have to compete. Here’s how to know the difference.
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Every once in a while, a technology comes along with so much potential that people can’t seem to stop talking about it. That’s fun and exciting, but it can also be confusing. Not all of the people who opine really know what they’re talking about and, as the cacophony of voices increases to a loud roar, it’s hard to know what to believe.
We’re beginning to hit that point with quantum computing. Listen to some and you imagine that you’ll be strolling down to your local Apple store to pick one up any day now. Others will tell you that these diabolical machines will kill encryption and bring global commerce to a screeching halt. None of this is true.
What is true though is that quantum computing is not only almost unimaginably powerful, it is also completely different than anything we’ve ever seen before. You won’t use a quantum computer to write emails or to play videos, but the technology will significantly impact our lives over the next decade or two. Here’s a basic guide to what you really need to know.
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Throughout America’s history, technological innovation has been key to security and prosperity. Whether it was through entrepreneurs like Thomas Edison, Henry Ford and Thomas Watson, or government programs like the Manhattan Project, the Apollo Program and the Human Genome Project, The United States has been on the cutting edge.
Today, as we enter a new era of innovation, America remains at the forefront of scientific discoveries in advanced areas such as artificial intelligence, synthetic biology, new computing architectures and materials science. Continued investment in science, both public and private, provides the “seed corn” for continued dominance in the 21st century.
Still, scientific advancement is not enough. We need entrepreneurs to start companies and mid-level technicians and engineers to implement technologies. The truth is that America’s human capital is being hollowed out and that’s becoming a serious problem that we need to address. Once we lose our competitive edge, we might never get it back.
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